Detection for Smart Home Devices’ Environment with Neural Network

As smart home and artificial intelligence technologies are developing rapidly, smart home devices contribute to better living quality and safer spaces. These smart devices are intelligent agents. They receive a variety of signals through sensors placed in ecobee’s thermostats, light switches and other smart devices and controls the heating and cooling, lighting, as well as providing important notifications. In this project, we would like to analyze sensory data and develop various machine learning solutions for characterization of the devices’ environment (e.g. object detection and audio classification). Currently, machine learning and deep learning algorithms have achieved significant improvement in building intelligent agents. We will apply them to assist ecobee’s products to better understand the environment and make better decisions.

Faculty Supervisor:

Roger Grosse

Student:

You-Syuan Liou

Partner:

Ecobee Inc.

Discipline:

Computer science

Sector:

Manufacturing

University:

University of Toronto